Path clustering for adaptive test
Takumi Uezono, Tomoyuki Takahashi, Michihiro Shintani, Kazumi Hatayama, Kazuya Masu, Hiroyuki Ochi, Takashi G. Sato · 2010
Adaptive test is one of the most efficient techniques that practically ensure high yield and reliability of designed chips. In this paper, a novel path-clustering method suitable for the adaptive test, in which test paths are altered according to the monitored process-parameters, is proposed. Considering the probability function of the die-to-die systematic process variation, the proposed method clusters path sets so that the total number of test-paths are minimized. For quantitative evaluation of different clusterings, figure of merit for clustering, which represents the expected number of test-paths at a particular test coverage, is also proposed. The proposed clustering is experimentally evaluated by applying to an industrial circuit. With our clustering, the average test paths in the adaptive test have been reduced to less than 50% compared with the ones of the conventional test.